Patients that become sensitized to HLA alloantigens by virtue of prior transplantation and rejection, blood transfusions or pregnancy experience longer waiting times before a none-reactive donor can be found. Decreased graft survival as compared to unsensitized recipients has also been observed. Accompanying this delay and outcome are the increased physical and psychological morbidity. We have developed a computerized predictive algorithm (KATS) that is based upon the identification of Acceptable versus Unacceptable private and public HLA antigens derived from the results of monthly serum screening. In essence the algorithm predicts selective mismatches for class I antigens in highly sensitized patients. Retrospective studies have validated the predictive power of the algorithm. In an initial retrospective analysis, in which each participating center utilized their own patients panel to examine 6 identical serum, a total of 292 cells were tested yet only 4 of the cells were 4 antigen identical with the serum donor. Utilizing the predictions, however, 215 crossmatch negative non- HLA class I were identified. In a multi-center retrospective study, the KATS program predicted a negative final crossmatch 95.3% and a successful transplant outcome 85.4% of the time. In another multi-center retrospective analysis, the predictive accuracy of a successful transplant in highly sensitized patients was also predicted. The same algorithm may be used to predict compatible donors for patients refractory to random platelet transfusion. We now propose to improve the prediction for a negative crossmatch and increase organ sharing bases on prospective predictions by the algorithm thereby decreasing the waiting time, increasing the rate of transplantation at those centers volunteering to mandatorily share kidneys on the basis of the KATS predictions and improving outcome. These results will be compared to a control group of equally sensitized stratified patients whose centers choose not to mandatorily share kidneys on this basis.